code: def get_incs(
      key,
      values: List[Any],
      data_list: List[BaseData],
      stores: List[BaseStorage],
  ) -> Tensor:
      repeats = [
          data.__inc__(key, value, store)
          for value, data, store in zip(values, data_list, stores)
      ]
      if isinstance(repeats[0], Tensor):
          repeats = torch.stack(repeats, dim=0)
      else:
          repeats = torch.tensor(repeats)
      return cumsum(repeats[:-1])
  
file_path: pytorch_geometric/torch_geometric/data/collate.py
imports: from collections import defaultdict
  from collections.abc import Mapping, Sequence
  from typing import Any, Dict, Iterable, List, Optional, Tuple, Type, TypeVar, Union
  import torch
  from torch import Tensor
  import torch_geometric.typing
  from torch_geometric import EdgeIndex
  from torch_geometric.data.data import BaseData
  from torch_geometric.data.storage import BaseStorage, NodeStorage
  from torch_geometric.edge_index import SortOrder
  from torch_geometric.typing import SparseTensor, TensorFrame, torch_frame, torch_sparse
  from torch_geometric.utils import cumsum, is_sparse, is_torch_sparse_tensor
  from torch_geometric.utils.sparse import cat
label_desc: Use image node_id 5 for calling a global function with example usage: get_incs(key, values, data_list, stores) and returns: cumsum